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Best of arXiv.org for AI, Machine Learning, and Deep Learning – September 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

The insideBIGDATA IMPACT 50 List for Q4 2021

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

Almost Half of Organizations Still Struggle with the Quality of their Data

Nearly half (48%) of organizations are still struggling to use and access quality data as underlying technology is failing to deliver on a number of critical functions. According to new research conducted by ESG in partnership with InterSystems, while organizations are looking to rapidly progress how they deliver data across the value chain, many are still faced with security (47%), complexity (38%), and performance (36%) challenges.

Exasol Report: 46% of CDOs Say that an Organization’s Expectations for the CDO Role are Too High and Misinformed

Our friends over at Exasol released the results of its landmark global study the defines the changes needed for today’s aspiring CDOs – and the organizations that recruit them- to prosper. The survey uncovered high demand for strong data leadership, as well as some confusion and uncertainty about the CDO role.

Working Smarter: Leveraging Machine Learning to Optimize CO2 Adsorption

In a recent study published in Environmental Science and Technology, a collaborative research team from Korea University and the National University of Singapore employed a machine learning-based approach that may guide the development of future porous carbon synthesis strategies. The scientists noted that there are three core factors influencing the CO2 adsorption properties in BWDPCs: the elemental composition of the porous solid, its textural properties, and the adsorption parameters at which it operates, such as temperature and pressure. However, how these core factors should be prioritized when developing BWDPCs has remained unclear, until now.

From Storage to Story: Delivering New Value by Unlocking the Power of Data

Our friends over at Kin+Carta know that optimizing the full value of data and figuring out where to start can be difficult. That is why the company has authored this whitepaper, “From Storage to Story: Delivering New Value by Unlocking the Power of Data,” on ways to make data work in four clear ways, while helping you take yours from Storage to Story, from modernization through to product optimization.

MLCommons™ Releases MLPerf™ Inference v1.1 Results

Today, MLCommons, an open engineering consortium, released new results for MLPerf Inference v1.1, the organization’s machine learning inference performance benchmark suite. MLPerf Inference measures the performance of applying a trained machine learning model to new data for a wide variety of applications and form factors, and optionally includes system power measurement.

DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain

The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

eBook: A Practical Guide to Using Third-Party Data in the Cloud

[Sponsored Post] To help you navigate a proliferating data landscape, AWS Data Exchange would like to present you with a copy of the new eBook, “A Practical Guide to Using Third-Party Data in the Cloud.” Learn how innovative teams are shifting their focus from data-driven business intelligence to accelerating insight-driven decision-making and now are turning to third-party datasets as a differentiator.